Abstracts from Dietetic Research Event – June 4-5, 2009
Bibliographic record
Abstract
Once again, the Dietitians of Canada (DC) national conference in Charlottetown provided an opportunity to showcase current research in dietetics and nutrition through the Canadian Dietetic Foundation for Dietetic Research (CFDR) Research Event. We had a large number of abstracts submitted this year, and included 24 oral presentations and 47 posters in the program. I was abstract editor 15 years ago when the DC conference was held in Charlottetown, and I was delighted to see the increased level of interest since then. It is critical for dietitians to be involved in research because it forms the framework and foundation for dietetics. We need to be the generators of the knowledge base for our profession, whether we are students, interns, collaborators, or principal investigators, and whether that knowledge is generated through measuring the impact of our practice, conducting basic research, or exploring the experiences and attitudes of those in our own profession. One of the most exciting things about research in nutrition and dietetics is the diversity of methods and approaches used. In fact, the abstracts included in the DC Conference 2009 are as diverse as our profession. Research presented will enhance our understanding of advances in nutrition education, national guidance, underlying mechanisms of chronic disease, and food service management, to name just a few areas. Settings also vary from public health to long-term care to university laboratories. Dietitians shared their “better practices” in such areas as nutrition screening and assessment, enhancing teaching and learning in undergraduate dietetic education and graduate studies, and health literacy and school nutrition. The “buzz” that these presentations and posters are sure to create will keep our profession vibrant and growing. On behalf of the membership of Dietitians of Canada, I would like to thank Dr. Candice Rideout and Kimberley Hernandez who, along with myself, constituted the small but hard-working Abstracts Review Committee. They not only gave up their time, they provided their expertise in judging a large number of abstracts. I would also like to thank the Canadian Foundation for Dietetic Research for its ongoing support of practice-based research in Canada. I am particularly grateful to Diana Sheh and Isla Horvath for shepherding us through the review process and the scheduling of presentations. Please join me in celebrating Canadian dietetic research represented in these abstracts of the poster sessions and oral abstract presentations from this year's CFDR Research Event.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.455 | 0.254 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".